RapidMiner provides an integrated environment for machine learning, data mining, text mining, predictive analytics and business analytics and is used for business and industrial applications as well as for research, education, training, rapid prototyping, and application development.
Predictive Analytics Software
RapidMiner : RapidMiner provides an integrated environment for machine learning, data mining, text mining, predictive analytics and business analytics and is used for business and industrial applications as well as for research, education, training, rapid prototyping, and application development. RapidMiner supports all steps of the data mining process including results visualization, validation and optimization.RapidMiner uses a client/server model with the server offered as Software as a Service or on cloud infrastructures. RapidMiner provides data mining and machine learning procedures including: data loading and transformation, data preprocessing and visualization, predictive analytics and statistical modeling, evaluation, and deployment.
RapidMiner is written in the Java programming language. RapidMiner provides a GUI to design and execute analytical workflows. Those workflows are called “Process” in RapidMiner and they consist of multiple “Operators”. Each operator is performing a single task within the process and the output of each operator forms the input of the next one. The engine can be called from other programs or used as an API. Individual functions can be called from the command line. RapidMiner provides learning schemes and models and algorithms from Weka and R scripts that can be used through extensions.
RapidMiner functionality can be extended with additional plugins. The Rapid Miner Extensions marketplace provides a platform for developers to create data analysis algorithms and publish them to the community.RapidMiner
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More Information on Predictive Analysis Process
For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.